7.2 Metaphors of the Mind

In 1980, George Lakoff and Mark Johnson published a book titled Metaphors We Live By (see also Lakoff, 1987; Johnson, 1987) in which they present a strong case that the way in which we perceive and think about a situation is a function of the metaphors we have adopted for and use in that situation. For example, Marshall (1988) has argued convincingly that the dominant metaphor in many schools is "School Is Work." We speak of students needing to work harder on their studies, to complete their homework, to earn a grade, and so forth. Teachers are trained to manage their classes and are often held accountable in terms of their productivity. These metaphors not only structure the way we think about schools, they also help create the world of the school. It is these metaphors, these grounding assumptions, that we want to examine.

To begin, we want to examine perhaps the most fundamental metaphor of all, our metaphor of mind. There have been many conceptions of mind throughout the history of philosophical and psychological inquiry (Gardner, 1985). Skipping lightly over several centuries of blank slates, wax tablets, telephone switchboards, and so forth, we want to summarize briefly two modern metaphors of mind before presenting our alternative.

7.2.1 Mind as Computer

First is the notion of "mind as computer" (MAC), the basic premise underlying early traditional artificial intelligence, but also much of instructional design and development. MAC assumes that the mind is an instantiation of a Turing machine, a symbol manipulation device (e.g., Newell & Simon: General Problem Solver, 1972). In this view, every cognitive process is algorithmic in the same sense that computer processes are algorithmic; i.e., the mind works by processing symbols according to rules. These symbols are entirely abstract and independent of any given individual's experience of them; i.e., the operation of the mind is completely independent of the person in whom it is contained. Meaning is mapped onto these symbols via our experiences in the world. Our understanding of the world is formed from a process of discovering reality "out there," interacting with it, and transferring that understanding into the mind, forming internal representations that determine our subsequent interactions with the environment. Symbols (or concepts) derive their meaning from their capacity to match (to a greater or lesser extent) aspects of reality. Any individual's internal representation will certainly depart from reality, but it does seem necessary to assume that, in principle, there must exist a conceptual framework that is entirely general and neutral, a single correct, completely objective way of representing the world. Learning is a process of information acquisition, processing according to innate or acquired rules, and storage for future use.

7.2.2 Mind as Brain

More recently cognitive scientists have proposed a metaphor of "mind as brain" (MAB), a view variously called connectionism or parallel distributed processing (see, for example, Rumelhart & McClelland, 1986). Connectionist models assume that symbols are learned consequences of particular experiences or interactions in the world, which are then mapped on or distributed across neural-like networks. Connectionism seeks to avoid the limitations of the MAC view and capitalize on precisely the experiential character of human concepts. It also deliberately links with our emergent knowledge of brain function; e.g., the brain would have to do massively parallel processing to accomplish even the most ordinary cognitive act, let alone the serial operations proposed by MAC models. Connectionism is the notion that intelligence emerges from the interactions of large numbers of simple processing units. Representations are not localized in some general~purpose symbol; rather they are distributed throughout a network of simple processing units according to patterns of activation that have emerged as a result of experience. Unlike MAC models, knowledge is not stored as a static copy of a pattern in long-term memory, with no real difference between what is retrieved and stored in working memory. Representation is an active process. What is stored in connectionist models are connection strengths between units that allow these patterns to be recreated (reconstructed). Consequently, learning is a matter of finding the right connection strengths so that the right pattern of activation will be produced under the right circumstances . . . , as a result of tuning of connections to capture the interdependencies between activations that the network is exposed to in the course of processing" (Rumelhart & McClelland, 1986, p. 32).

MAC and MAB models are alike in that both characterize mind as separate from the environment and as information processing bound within individuals. A major difference is that knowledge is a matter of storage and retrieval according to rules in the MAC view, but a function of distributed connection strengths and network activation for the MAB position. It is this difference that sets the stage for the possibility of some fresh thinking about the teaching/ learning process.

7.2.3 Mind as Rhizome

The alternative we wish to propose here builds on the MAB metaphor but moves the mind out of the head and deliberately blurs or obliterates such common distinctions as environment/ individual, inside/outside, and self/other. We will label our view "mind as rhizome" (MAR), a metaphor inspired by Umberto Eco (1984, p. 81; see also Deleuze & Guattari, 1983). A rhizome is a root crop, a prostrate or underground system of stems, roots, and fibers whose fruits are tubers, bulbs, and leaves. A tulip is a rhizome as is rice grass, even the familiar crab grass. The metaphor of rhizome specifically rejects the inevitability of such notions as hierarchy, order, node, kernel, or structure. The tangle of roots and tubers characteristic of rhizomes is meant to suggest a form of mind where:

• Every point can and must be connected with every other point, raising the possibility of an infinite juxtaposition. There are no fixed points or positions, only connections (relationships).
• The structure is dynamic, constantly changing, such that if a portion of the rhizome is broken off at any point it could be reconnected at another point, leaving the original potential for juxtaposition in place.
• There is no hierarchy or genealogy contained as where some points are inevitably superordinate or prior to others.
• The rhizome whole has no outside or inside but is rather an open network that can be connected with something else in all of its dimensions.

The notion of a rhizome is a difficult one to imagine, and any attempt to view it as a static picture risks minimizing its dynamic, temporal, and even self-contradictory character. Eco (1984) has labeled the rhizome as "an inconceivable globality" to highlight the impossibility of any global, overall description of the network. Since no one (user, scientist, or philosopher) can describe the whole, we are left with "local" descriptions, a vision of one or a few of the many potential structures derivable from the rhizome. Every local description of the network is an hypothes ' is, an abduction (see Shank, 1987) constantly subject to falsification. To quote Eco:

Such a notion ... does not deny the existence of structured knowledge; it only suggests that such a knowledge cannot be recognized and organized as a global system; it provides only "local" and transitory systems of knowledge which can be contradicted by alternative and equally "local" cultural organizations; every attempt to recognize these local organizations as unique and "global" --ignoring their partiality--produces an ideological bias (1984, p. 84).

This last statement emphasizes the point that we are not proposing the metaphor of rhizome for an individual mind, but to minds as distributed in social, cultural, historical, and institutional contexts. Except as a degenerate case, there is no such thing as a single mind, unconnected to other minds or to their (collective) social-cultural constructions. Thinking, or whatever we choose to call the activity of mind, is always dialogic, connected to another, either directly as in some communicative action or indirectly via some form of semiotic mediation: signs and/or tools appropriated from the sociocultural context.

Wertsch (1991), drawing inspiration from Vygotsky and Bakhtin, has argued this case very well (without invoking the metaphor of the rhizome), and we will present his view more fully. For our purposes here, we want to stress the potential connectivity implied by the MAR metaphor. We are connected to other people individually but also collectively, as in the speech communities or social languages in which we are all embedded. We are connected to the sociocultural milieu in which we operate, a milieu characterized by the tools (computers, cars, television, and so forth) and signs (language, mathematics, drawing, etc.), which we may appropriate for our thinking. Thus thinking is not an action that takes place within a mind within a body, but rather at the connections, in the interactions. But it is worth saying again that this thinking is always "local," always a limited subset of the potential (unlimited) rhizomous connections.

Learning, then, is neither a matter of discriminating the symbols of the world and the rules for manipulating them nor of activating the right connections in the brain. It is, rather, a matter of constructing and navigating a local, situated path through a rhizomous labyrinth, a process of dialogue and negotiation with and within a local sociocultural context. Although this analogy fails if pushed too far, the connectivity we have in mind is a bit like the World Wide Web (WWW). While the "results" of a connection to WWW is experienced via an interface with one's local workstation, that experience is possible only as a result of connections with many (potentially an infinite number of) servers all over the world. The local workstation both contributes to (constructs) and is constructed by its connections.